Open AccessThe Attention to Detail Test: Measurement Precision and Validity Evidence for a Performance-Based Assessment of Attention to Detail
Author(s) -
Brent A. Stevenor,
Michael J. Zickar,
Fletcher Wimbush,
Weston Beck
Publication year - 2022
Publication title -
personnel assessment and decisions
Language(s) - English
Resource type - Journals
ISSN - 2377-8822
DOI - 10.25035/pad.2022.01.006
Subject(s) - incremental validity , psychology , construct validity , test (biology) , curse of dimensionality , predictive validity , construct (python library) , criterion validity , measure (data warehouse) , facet (psychology) , computer science , personality , cognitive psychology , machine learning , psychometrics , social psychology , big five personality traits , data mining , clinical psychology , paleontology , biology , programming language
We report on the dimensionality, measurement precision, and validity of the Attention to Detail Test (ADT) designed to be a performance-based assessment of people’s ability to pay attention to detail. Within the framework of item response theory, we found that a 3PL bifactor model produced the most accurate item parameter estimates. In a predictive validity study, we found that the ADT predicted supervisor ratings of subsequent overall job performance and performance on detail-oriented tasks. In a construct-related study, scores on the ADT correlated most strongly with the personality facet of perfectionism. The test also correlated with intelligence and self-reported ACT scores. The implications of modeling the ADT as unidimensional or multidimensional are discussed. Overall, our findings suggest that the ADT is a valid measure of attention to detail ability and a useful selection tool that organizations can use to select for detail-oriented jobs.